Method and system for integrated link adaptation and power control to improve error and throughput performance in wireless packet networks

ABSTRACT

The invention provides a system that implements an algorithm for integrated link adaptation and power control to achieve specified error rates and to improve an overall throughput for real-time applications in wireless packet networks. The system initially divides wireless terminals into groups according to their signal path gains. Afterwards, the system can periodically adapt transmissions (i.e., link adaptations) based on the required error rates, actual error statistics and average transmission power for each wireless terminal group. Furthermore, transmission power can be adjusted by an enhanced Kalman-filter method to ensure successful reception.

RELATED APPLICATIONS

This application is a Continuation of, and claims priority from, U.S.patent application Ser. No. 12/381,292 filed Mar. 10, 2009, now U.S.Pat. No. 7,920,505 which is a continuation of U.S. patent applicationSer. No. 09/570,097 filed in the USPTO May 12, 2000, now U.S. Pat. No.7,502,340.

BACKGROUND OF THE INVENTION

1. Field of Invention

The present invention relates to a method and system for integrated linkadaptation and power control in wireless networks to improve error andthroughput performance of a wireless network.

2. Description of Related Art

As telecommuting and Internet access become increasingly popular,customer demand for broadband network services is increasing. In thevery near future, broadband services are also expected to supportreal-time, multimedia services such as voice, image and video. Wirelessaccess is one of the approaches to providing such services. Inparticular, the European Telecommunications Standards Institute is inthe process of establishing the protocol standards for the Enhanced Datarates for GSM Evolution (EDGE) system as a third generation of wirelessnetworks for high-speed services. Using packet-switching technology, andmultiple modulation and coding levels (to be referred to as modulationlevels below for brevity), the EDGE system employs a link-adaptationtechnique to adapt packet transmissions to one of several modulationlevels where the highest data rate can exceed 384 Kbits/sec.

The idea of link adaptation is to adapt the modulation encoding levelsaccording to the channel and interference conditions in order to improvedata throughput. For example, when the channel and interferenceconditions are poor, a low modulation level (i.e., few information bitsper symbol) and/or heavy coding should be used in a packet transmissionto enable correct signal detection. On the other hand, if the channelsituations are more favorable, a high modulation level and/or lightcoding can be used to increase the data rate.

Due to unreliable radio links, it is challenging to assure a quality ofservice (QoS) in terms of packet error rate (PER) in a wireless network.For real-time services, such as IP voice, music and video, stringentdelay requirements severely limit or even preclude re-transmission oflost packets. Therefore, tight delay requirements often translate intostringent requirements for the PER. As a result, in order to supportsuch real-time services, it is important to design wireless networkssuch that the required QoS can be delivered to the users.

Currently, it is known that link adaptation is helpful in delivering aparticular QoS. Specifically, when a channel condition is poor,transmitters can lower modulation levels to decrease the requirement ofthe signal-to-interference-plus-noise ratio (SINR) for correct signaldetection. Lowering the SINR requirements increases the probability ofsuccessful reception, and therefore helps to meet particular PERobjectives.

However, especially for interference-limited systems with sufficienttraffic load, adapting even to the lowest modulation level may notalways guarantee meeting the specified PER. In this case, increasing atransmission power can improve signal strength, and therefore the SINRat the receivers. Hence, power control can be viewed as performing anactive role in delivering the expected PER to users, while linkadaptation or adaptive modulation plays a passive (or reactive) role.

Accordingly, a key design problem for a wireless packet network, such asthe EDGE system, is how to maximize the overall network throughput overthe choice of modulation levels, and transmission power, subject tomeeting given PER requirements.

SUMMARY OF THE INVENTION

The present invention provides a system and method for implementing aheuristic algorithm for integrated link adaptation and power control toachieve specified error rates and to improve an overall throughput forreal-time applications in wireless packet networks. The method initiallydivides wireless terminals into groups according to their signal pathgains. Afterwards, the method can periodically adapt transmissions(i.e., link adaptations) based on the required error rates, actual errorstatistics and average transmission power for each wireless terminalgroup. Furthermore, transmission power can be adjusted by an enhancedKalman-filter method to ensure successful reception.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention is described in detail with regard to the followingFigures, in which like elements are referred to with like numerals, andin which:

FIG. 1 is an exemplary block diagram depicting one cell of a wirelesscommunication network in accordance with the present invention;

FIG. 2 shows a cell layout and channel assignment for a group of cells;

FIG. 3 is a graph showing an exemplary relationship between interferenceand signal path gain from a mobile terminal and a base station;

FIG. 4 shows exemplary modulation levels for corresponding SINRdetection requirement and data throughput rates;

FIG. 5 is a table showing a comparison of various link-adaptationmethods;

FIG. 6 is a probability distribution of various modulation levels; and

FIG. 7 is a table showing the performance of a terminal-grouping methodat various traffic loading.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

FIG. 1 is an exemplary block diagram depicting one cell 107 of awireless cellular communication network. A base station 105 operateswithin the cell 107. The base station 105 contains a controller 110, amemory 115, a transponder 120, and an antenna 125. Numerous mobileterminals 130 located within the cell 107 communicate with the basestation 105 via antenna 125, an uplink channel 137 and a downlinkchannel 135.

For the purposes of this application, a number of environmental andsystem conditions can be assumed. In particular, the uplink channel 137and the downlink channel 135 are each subject to attenuation due to pathgain (effectively, attenuation) between the base station 105 and themobile terminal 130. Effectively, the path gain is the sum of the pathloss and the shadow fading for the radio link.

Furthermore, a medium-access control (MAC) protocol is used within eachcell 107, which allows at most one mobile terminal 130 in each of thecells 107 to transmit at a time. That is, no data contention occurswithin the same cell 107. Therefore, only one mobile terminal 130communicates with the base station 105 in a given time slot. Due to thelarge volume of data involved, the base station 105 typically cannotexchange control and scheduling information with another base station105 operating in a different cell 107. Finally, the interference powerfor a particular time slot can be measured at the base station 105 andmobile terminals 130, but may include noise and errors.

In operation, communications between the base station 105 and the mobileterminals 130 are transmitted using an integrated link adaptation andpower control to achieve specific packet error rates (PER) and toimprove overall throughput for real-time applications in wireless packetnetworks. There are two key factors for efficient link-adaptationschemes. First, in order to maximize the network throughput, it isdesirable to have a link-adaptation technique that adapts quickly tochanges of radio conditions. On the other hand, to guarantee therequired PER, it is advantageous to adapt the link according to anactual error performance or error statistics. Since error statistics canrequire a long time to accumulate, link adaptation based on per-usererror performance is often too slow for responding to changes of achannel's condition. Accordingly, the present invention can estimate theper-user error performance by dividing all the mobile terminals 130 ineach cell 107 into groups. Once divided, a link adaptation technique canbe performed on a per-terminal-group basis according to an errorperformance of each group. In this manner, the error statisticscollection time can be shortened significantly, and thereby enable aquick link adaptation to improve data throughput while meeting thenecessary error requirements.

In a preferred embodiment, the mobile terminals 130 can be grouped bysignal path gains. The quality of a radio link between a mobile antenna125 and its associated base station 105 can typically be characterizedby three parameters: the signal path gain (including shadow fading), thesignal transmission power and interference power. However, in packetnetworks, both the signal transmission and interference power areconstantly changing. By contrast, the signal path gain is generally themost intrinsic parameter for link quality. Accordingly, with the presentinvention, it is preferable to use the signal path gain as a criterionfor the terminal grouping. The mobile terminals 130 of the same groupare generally expected to have a similar link quality and to cause asimilar amount of interference with others.

Another reason for using signal path gain as the grouping criterion isthat the signal and interference path gains are almost uncorrelated. Byway of example, consider the cellular layout and channel assignment of afrequency reuse factor of 2 in FIG. 2, where 2000 terminals are randomlypopulated at fixed locations in each cell 107. With typical radiopropagation assumptions, FIG. 3 shows the relationship between thesignal path gain (shadowing included) from a mobile terminal 130 to itsassociated base station 105 and the sum of the path gains from themobile terminal 130 to all other co-channel base stations 105, whichreceive interference from the mobile terminal 130 for uplinktransmission. The sum of the interfering path gains reflects thepotential impacts of interference caused by the mobile terminals 130.

From FIG. 3, it can be found that the signal path gain and the sum ofinterfering path gains have a very small correlation coefficient of0.018. Such uncorrelated relationship is desirable for the purposes ofthe present invention. Otherwise, if the correlation between the signalpath gain and the sum of interfering path gain is a strong positivecorrelation, the link adaptation based on such a terminal group basismay make unstable changes in the modulation level.

One method of performing the mobile terminal 130 grouping is todetermine a range of possible signal path gain for a given network, thendivide the range into several regions. It should be noted that theregion need not necessarily be uniform. Accordingly, a group willinclude the mobile terminals 130 with corresponding signal path gains ineach region. In order to speed up the collection of error statisticsuniformly, it is desirable to have a roughly equal number of mobileterminals 130 in each group. Furthermore, the number of mobile terminalgroups can be chosen to be equal to the number of modulation levels inthe system so that each group may be transmitting or receiving at adistinct modulation level. Furthermore, the number of groups should beselected based on the number of active mobile terminals 130. If thereare too few mobile terminals 130 per group, then the purpose of themobile terminal grouping in terms of shortening the statistic collectionis defeated.

In operation, for uplink transmissions for each cell 107 or co-channelsector, the base station 105 as the receiver continuously collects errorstatistics, and computes a packet error rate (PER) for every K packettransmissions from terminals of each group. In addition, the basestation 105 keeps tracks of the average transmission power p of the Kpacket transmissions, regardless of their modulation level, for eachterminal group.

Every time K packets have been transmitted by mobile terminals 130 ofthe same group and received by the base station, the base stationdetermines a packet error rate (PER) for the group. If the PER is higherthan a required PER, the base station can adjust the modulation leveldown by one level for the next K packet transmission by the mobileterminals 130 in the group. The purpose of stepping down the modulationlevel is to lower the required signal-to-interference-to-noise-ratio(SINR) for correct reception, thereby improving the PER when necessary.

Since the base station instructs the mobile terminals to transmit atappropriate power level, the base station has the knowledge of thetransmission power. If the average transmitted power of the last Kpackets p is less than a given threshold p_(t) (e.g., 15 dBm), the basestation can step up the modulation level by one level for the next Ktransmission from the terminal group. The idea is to utilize unusedpower and to increase data rate, if possible.

In order to achieve the PER requirement, each modulation level isassociated with a nominal SINR target. Using an enhanced Kalman-filterpower control, the transmission power is adjusted for each time slot toachieve the SINR target for the adapted modulation level. That is, thetransmission power for time slot n is set to bep(n)=γ*δ(n)ĩ(n)/g(n)  (1)where γ* is the SINR target for the chosen modulation level, ĩ(n) is theinterference-plus-noise power (mW) in slot n predicted by the Kalmanfilter, δ(n) is an error margin, and g(n) is the (estimated) path gainbetween the terminal that transmits in slot n and its base station.

The error margin δ(n) is obtained by tracking the accuracy of theinterference power predicted by the Kalman filter. More precisely, let Δ(a random variable in dB) be the error of the Kalman-filer predictionand the error for slot n beE(n)=I(n)−Ĩ(n)  (2)where I(n) and Ĩ(n) are the measured and predictedinterference-plus-noise power in dBm for slot n, respectively. Based onthe E(n)'s, the cumulative probability function (CDR) for Δ isapproximated. Towards this end, let there be J intervals of predictionerror and let the range of the j^(th) interval be (a_(j), a_(j+1)). Foreach time slot n>0 and each j=1 to J, compute the following:

$\begin{matrix}{P_{n}^{j} = \left\{ \begin{matrix}{\phi\; P_{n - 1}^{j}} & {{{if}\mspace{14mu}{E(n)}} > a_{j + 1}} \\{{\phi\; P_{n - 1}^{j}} + 1 - \phi} & {otherwise}\end{matrix} \right.} & (3)\end{matrix}$where P_(n) ^(j) is the approximate probability of Δ≦a_(j+1) based onthe error sequence E(n) up to slot n with P_(o) ^(j)=1 for all j=1 to Jinitially, and φ is a properly chosen parameter between 0 and 1. LetΔ(n) be a specified ω^(th) percentile (e.g., for 90th percentile, ω=0.9)of Δ based on the error statistics up to slot n. We approximateΔ(n)≈a_(k) where k is the smallest from 1 to J such that P_(n) ^(k)≧w.Let δ(n) and ĩ(n) be the linear-scale equivalent of Δ(n) and ĩ(n),respectively. The corresponding percentile of theinterference-plus-noise power in mW is the product of ĩ(n) (predicted bythe Kalman filter) and δ(n). Accordingly, the transmission power forslot n is determined by equation (1).

In essence, the term δ(n) represent an error margin, which depends onthe accuracy of the interference prediction by the Kalman filter and thespecified confidence probability ω. Nevertheless, the error margin ischosen dynamically and appropriately with a goal of delivering the SINRtarget γ* regardless of the actual message length and control delay.

Furthermore, after the modulation level for each terminal has beenadjusted, a minor adjustment (e.g., a fraction to a couple of dB's) canbe added to the nominal target to obtain the actual SINR target γ* forproper power control by equation (1). Such an adjustment is revisedperiodically and relatively slowly (i.e., similar to the CDMA outer-looppower control) to ensure required error performance for individualmobile terminals 130.

An example of enhanced Kalman-filter power control with an error marginis disclosed in application Ser. No. 09/460,993 filed on Dec. 15, 1999,entitled “A Method and System for Power Control in Wireless NetworksUsing Interference Prediction with an Error Margin,” which isincorporated herein by reference in its entirety.

It is worth noting that the base station 105 steps down the modulationlevel due to unsatisfactory PER performance, and moves the modulationlevel up in a case of under-utilized power. Additionally, it is possiblethat the PER does not meet the required performance and the averagetransmission power is also below the threshold p_(t). This can be due tothe fact that the Kalman filter cannot predict interference-plus-noisepower accurately enough. Since the power control includes the errormargin δ(n), which possibly changes from one time to the next, slightincreases in the δ(n) because of the inaccurate predictions (thus usinga small fraction of unused power) may be enough to meet the PERrequirement. Therefore, the modulation level remains unchanged for thosecases, with a hope that the PER becomes satisfactory for the next Kpacket transmissions by power control.

In order to further describe the performance of the present invention, acomputer simulation is used to describe the performance of the proposedtechnique for link adaptation and power control based on the terminalgrouping, which is referred to as the terminal-grouping method. Thecomputer simulation simulates a cell layout and interleaved channelassignment (ICA) with a frequency reuse factor of 2, as shown in FIG. 2.Each cell 107 is divided into 4 sectors 202, each of which is served bya base station antenna at the center of the cell 107. The beamwidth ofeach base station antenna is 60°, while terminals have omni-directionalantennas. Each radio link between a terminal 130 and its base station105 is characterized by a path-loss model with an exponent of 4 andlognormal shadow fading with a standard deviation of 8 dB. Fast fadingwas not considered in this simulation. Cell 107 radius is assumed to be1 Km and the path loss at 100 m from the cell center is −70 dB. Thermalnoise power at the receiver is fixed and equal to −110 dBm. Each sector202 is populated with 500 terminals randomly and each of them selectsthe base station 105 that provides the strongest signal power. Forconvenience, terminals in all cells 107 are assumed to be synchronizedat the slot boundary for transmission. Furthermore, unless statedotherwise, we assume 100% traffic load in this simulation. That is,there are always terminals 130 ready for transmission in each co-channelsector 202. Message length is assumed to be Pareto distributed with anaverage of 10 packets.

The enhanced Kalman-filter method, described above, is used to controltransmission power for each time slot. For tracking the CDF of theprediction error Δ, φ in equation (3) is set to be 0.999 (approximatelyequal to tracking the error over a sliding window of 1,000 slots) andthe number of error intervals J is 100. For a given PER requirementP_(R), the ω^(th) percentile of the prediction error with ω=1−P_(R) isused in determining the error margin δ(n) for adjusting power inequation (1). For example, when P_(R)=0.02, δ(n) is the 98^(th)percentile of the predication error. In any event, transmission power islimited between 0 to 30 dBm. The average power threshold, p_(t), fordetermining the stepping up of the modulation level, described above, is15 dBm. Two adjustable parameters for the Kalman-filter method, W and η,are set to be 30 and 0.5 respectively. The simulation also assumes thatinterference power in one time slot can be measured accurately and usedto determine the power for a next slot.

Furthermore, for the purposes of the simulation, we assume that thesystem has six modulation levels. The SINR detection requirements andthe corresponding data throughput for each modulation level are shown inFIG. 4. For example, for a packet transmission using modulation level 1,if the SINR at the receiver is greater than 10 dB, the packet isreceived successfully and the data throughput is 22.8 Kbps. Naturally,the SINR requirements are also used as the targets γ* for variousmodulation levels to control power in equation (1). For simplicity, slowand minor adjustment of SINR targets for individual terminals is notconsidered in the simulation.

With 6 modulation levels, all 500 terminals in each sector 202 aredivided into six groups of equal size according to their signal pathgain. Initially, the group with the weakest to the strongest signal pathgain uses modulation level 1 to 6 for transmission, respectively. Then,according to the algorithm, the modulation level is re-adapted everyK=1,000 packets transmitted by each terminal group. For each parametersetting, the simulation model was run for 0.4 million time slots andperformance results presented below were obtained for the middle cell inFIG. 2.

To set up a basis for comparison, the simulation considered a simplelink-adaptation scheme without power control (PC) that chooses themodulation level according to the SINR measurement of the previous timeslot. This method is referred to as the SINR-based adaptation method.Specifically, the scheme compares the SINR measurement with thedetection requirements in FIG. 4. For example, when the measurement liesbetween 12 and 16 dB, modulation level 2 is used for transmission in thenext time slot. Every sector 202 makes such selection for itstransmitting terminal independently. This SINR scheme is referred to asCase A in FIG. 5. Cases B to D are identical to Case A, except that theenhanced Kalman method is now used to control transmission poweraccording to the various PER requirements P_(R). To assist in theunderstanding of the technique, Cases E to G correspond to thelink-adaptation method by terminal grouping without power control, whileCases H to J represent the technique of the present invention. FIG. 5presents the throughput, the PER for packets transmitted at differentmodulation levels, and the overall PER averaged over all levels forthese cases.

To begin with, it can be seen from FIG. 5 that when power control is notused, Cases A and E to G for both the SINR and terminal-grouping methodscannot control the PER effectively. For the SINR method, it is sobecause the previous SINR measurements may not accurately predict SINRperformance in future time slots because of the burstiness of packettransmission in the wireless packet environment. As a result, the chosenmodulation level may not lead to successful packet reception as theradio conditions can change drastically in time. As for Cases E to G,the terminal-grouping method adapts the modulation level according tothe requirement P_(R). However, the scheme is not effective indelivering the PER performance because the link adaptation takes placeonly periodically and the radio conditions can vary significantly fromone time slot to another during the adaptation period.

As the results for Cases B to D show, the SINR scheme with the enhancedKalman power control is still not quite effective because SINRmeasurements may not accurately reflect future link quality. Incontrast, according to the specified PER requirement P_(R) the proposedalgorithm adapts transmissions at appropriate modulation levels, andadjusts transmission power to meet the SINR detection threshold.Consequently, as shown in FIG. 5, the PER performance for Cases H to Jgenerally comes very close to the PER target P_(R). One can observe thatthe PER for transmission at modulation level 1 in Case H is noticeablyhigher than the required 2% PER. This reveals that the radio conditionsmay not support the very stringent PER performance for a very smallfraction of terminals. In any event, the overall PER of 2.7% is veryclose to the target of 2% in that case. As intuitively expected, whenP_(R) becomes less stringent, the throughput is increased in Cases H toJ.

It is important to point out that the ability to control the PER to meetthe specified targets by the proposed algorithm comes at a price ofreduced throughput. In fact, this represents an interesting tradeoffbetween maximizing throughput and controlling PER performance. Forexample, one can see from FIG. 5 that the SINR method in Cases A to Dyields almost ⅓ more throughput than Cases H to J of theterminal-grouping method. Nevertheless, to meet the PER requirements forspecific applications, network designers can use the integratedalgorithm for power control and link adaptation to achieve a desirabletradeoff between the PER and throughput.

FIG. 6 presents the probability distribution of the modulation levelsfor actual packet transmission for the proposed algorithm for varioustarget PER. For example, for terminal group 4, the probability of packettransmission using modulation level 4 is 0.178, 0.338 and 0.454 for thetarget PER of 5%, 10% and 15%, respectively. This confirms the expectedoperations of the proposed algorithm because for less stringent PERrequirements, the algorithm will tend to step up the modulation levelfor transmission.

Finally, we study the packet error and throughput performance of theproposed algorithm with partial traffic loading. For a given loading,after a terminal completes a message transmission, its associated sectorremains idle for a random number of time slots before a next terminal inthe sector is allowed to start a new message transmission. The durationof an idle period is geometrically distributed and its average isdetermined according to the average message length and the trafficloading.

FIG. 7 presents the measured PER and throughput of the proposedalgorithm for various target (required) PER and traffic load conditions.First, it can be seen that the proposed algorithm indeed can deliver therequired PER performance as the measured PER comes very close to thetarget values. Second, it is interesting to note that the throughputincreases as traffic load decreases. This is a very desirable featurebecause the power control in the proposed algorithm will detect reducedinterference power when traffic load decreases, thus lowering thetransmission power needed to yield the SINR target γ* in equation (1).In turn, comparing the average transmission power with a fixed thresholdp_(t) will likely step up the modulation level for transmission, whichresults in increased data throughput. Third, FIG. 7 reveals that for agiven traffic load, the throughput does not always improve as the targetPER is increased (relaxed). Evidently, for very stringent PERrequirements, the algorithm will force most of the transmissions usingthe more robust modulation, which yields a low throughput. On the otherhand, when the required PER is too high, the algorithm tends to allowtoo many packets transmitted using high modulation levels, which resultin unsuccessful reception and lowered throughput. For a given trafficload, there appears to be an “optimal” target PER that can maximize thenetwork throughput.

While this invention has been described in conjunction with the specificembodiments thereof, it is evident that many alternatives,modifications, and variations will be apparent to those skilled in theart. Accordingly, preferred embodiments of the invention as set forthherein are intended to be illustrative, not limiting. Various changesmay be made without departing from the spirit and scope of the inventionas described in the following claims.

What is claimed is:
 1. A method executed in a base station thatinteracts with terminals, comprising the steps of: determining range ofsignal path gains for said terminals, dividing said range into aplurality of gain non-overlapping intervals, each having a lowerboundary signal path gain and an upper boundary signal path gain;assigning to each interval those of said terminals (group of terminals)that have a signal path gain between the lower and upper boundaries ofsaid each interval; specifying an associated modulation level to thegroup of terminals that are assigned to each of the intervals, to beused by said terminals when transmitting to said base station, for eachgroup of terminals, based on every set of K packets that are receivedfrom terminals in said each group, computing an associated group packeterror rate, which is a collective packet error rate of said group ofterminals as experienced at said base station; and specifying to theterminals in said group of terminals to modify their mode of operationin a direction that decreases throughput of data from said terminals, ifthe computed associated group packet error rate is above a specifiedgroup packet error rate.
 2. The method of claim 1 where said intervalsare chosen based on number of modulation levels that may be employed. 3.The method of claim 1 where said intervals are chosen to include anumber of terminals that is not lower than a preselected number.
 4. Themethod of claim 1 where said step of specifying to the terminals in saidgroup to modify their mode of operation includes specifying, a powerlevel at which to transmit.
 5. The method of claim 4 where said powerlevel for each of the terminals in said group is adjusted to achieve atarget signal-to-interference-to-noise ratio.
 6. The method of claim 5where, following computing said power level for each of the terminals insaid each group, computing an average power for said groups ofterminals, and stepping up the modulation level of the terminals in saidgroup by one level if the computed average power is less than apreselected level.
 7. The method of claim 1 where said step ofspecifying to the terminals in said group of terminals to modify theirmode of operation includes specifying a current modulation level forsaid each group of terminals.
 8. The method of claim 1 where saidspecifying to the terminals in said group to modify their mode ofoperation includes specifying both a current modulation level for saidgroup of terminals and transmission power by said terminals.
 9. Themethod of claim 1 where said step of specifying to the terminals in saidgroup of terminals to modify their mode of operation includes modifyingthe mode of operation in a direction that increases throughput of datafrom said terminals.
 10. The method of claim 1 where said step ofspecifying an associated modulation level specifies a differentmodulation level to the groups of terminals that are assigned to thedifferent intervals.